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Carnegie Mellon Robotics Institute

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Abstract

We compare two recently proposed approaches for representing probability distributions over the space of permutations in the context of multi-target tracking. We show that these two representations, the Fourier approximation and the information form approximation can both be viewed as low dimensional projections of a true distribution, but with respect to different metrics. We identify the strengths and weaknesses of each approximation, and propose an algorithm for converting between the two forms, allowing for a hybrid approach that draws on the strengths of both representations. We show experimental evidence that there are situations where hybrid algorithms are favorable.

Notes

Number of pages: 16

Text Reference

Xiaoye Jiang, Jonathan Huang, and Leonidas Guibas, "Fourier-Information Duality in the Identity Management Problem," The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML 2011), September, 2011.

BibTeX Reference

@inproceedings{Huang_2011_6869,
   author = "Xiaoye Jiang and Jonathan Huang and Leonidas Guibas",
   title = "Fourier-Information Duality in the Identity Management Problem",
   booktitle = "The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML 2011)",
   month = "September",
   year = "2011",
}

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